Abstract
Inhibitory networks are now recognized as being the controllers of several brain rhythms. However, experimental work with inhibitory cells is technically difficult not only because of their smaller percentage of the neuronal population, but also because of their diverse properties. As such, inhibitory network models with tight links to the experimental data are needed to understand their contributions to population rhythms. However, mathematical analyses of network models with more than two cells is challenging when the cellular models involve biophysical details. We use bifurcation analyses and simulations to show that two-cell analyses can quantitatively predict N-cell (N = 20, 50, 100) network dynamics for heterogeneous, inhibitory networks. Interestingly, multistable states in the two-cell system are manifest as different and distinct coherent network patterns in the N-cell networks for the same parameter sets.
Similar content being viewed by others
References
Bartos M, Vida I, Frotscher M, Geiger JRP, Jonas P (2001) Rapid signaling at inhibitory synapses in a dentate gyrus interneuron network. J. Neurosci. 21: 2687–2698.
Bartos M, Vida I, Frotscher M, Meyer A, Monyer H, Geiger JRP, Jonas P (2002) Fast synaptic inhibition promotes synchronized gamma oscillations in hippocampal interneuron networks. Proc. Natl. Acad. Sci., 99(20): 13222–13227.
Doedel EJ (1981) AUTO: A program for the automatic bifurcation analysis of autonomous systems. Congr. Numer., 30: 265–284.
Ermentrout GB (2002) Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students. SIAM, Philadelphia, http://www.math.pitt.edu/~bard/xpp/xpp.html.
Freund TF (2003) Interneuron diversity series: Rhythm and mood in perisomatic inhibition. Trends Neurosci. 26(9): 489–495.
Golomb D, Hansel D, Mato G (2001) Mechanisms of synchrony of neural activity in large networks. In: S. Gielen, M. Moss, eds., Handbook of Biological Physics, Vol. 4, Elsevier Science B.V., Amsterdam, pp. 887–968.
Klausberger T, Magill P, Ma’rton M, Roberts J, Cobden P, Buzsa’ki G, Somogyi P (2003). Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo. Nature 421: 844–848.
Lewis TJ, Rinzel J (2003). Dynamics of spiking neurons connected by both inhibitory and electrical coupling. J. Comput. Neurosci. 14(3): 283–309.
McBain C, Fisahn A (2001). Interneurons unbound. Nature Rev. Neurosci. 2: 11–23.
Murray PA (2004) Capturing details of short-term synaptic plasticity in simple schemes. Master’s Thesis, University of Toronto.
Skinner FK, Chung JYJ, Ncube I, Murray PA, Campbell SA (2004). Using heterogeneity to predict inhibitory network model characteristics. J. Neurophysiol. (in press).
Skinner FK and Liu JB (2003). NNET: Linking small and large-scale network models. Neurocomputing 52–54: 381–387.
Tiesinga PHE, Jose’ JV (2000). Robust gamma oscillations in networks of inhibitory hippocampal interneurons. Network: Comput. Neural Syst. 11: 1–23.
Wang X-J, Buzsa’ki G (1996) Gamma oscillation by synaptic inhibition in a hippocampal interneuronal network model. J. Neurosci., 16: 6402–6413.
White, JA, Chow CC, Ritt J, Soto-Treviño C, Kopell N (1998) Synchronization and oscillatory dynamics in heterogeneous, mutually inhibited neurons. J. Comput. Neurosci. 5: 5–16.
Wu C, Luk WP, Gillis J, Skinner FK, Zhang L (2004) Size does matter: Generation of intrinsic network rhythms in thick mouse hippocampal slices. J. Neurophysiol. (in press).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Skinner, F.K., Bazzazi, H. & Campbell, S.A. Two-Cell to N-Cell Heterogeneous, Inhibitory Networks: Precise Linking of Multistable and Coherent Properties. J Comput Neurosci 18, 343–352 (2005). https://doi.org/10.1007/s10827-005-0331-1
Received:
Revised:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/s10827-005-0331-1